Title :
Processing the uncertainty: Quality-aware data stream processing for dynamic context models
Author_Institution :
OFFIS, Oldenburg, Germany
Abstract :
Current autonomic vehicles in outdoor scenarios perform mobility operations with walking speed to ensure safety. For a faster mobility of autonomous vehicles, concrete knowledge of the environment is needed. This will be achieved through a dynamic context model based on sensor data with uncertainties from the environment. These uncertainties arise through existential uncertainty, consistency, and co/variance of and between the sensor data. To allow a flexible processing and to allow different approaches for object detection, object classification, and object tracking, data stream management technology is used. Therefore, a new algebra and operators based on the relational algebra are defined to preserve and process the uncertainties about the sensor data.
Keywords :
image classification; mobile computing; mobile robots; object detection; object tracking; relational algebra; robot vision; sensor fusion; autonomic vehicles; data stream management technology; dynamic context models; mobility operations; object classification; object detection; object tracking; quality-aware data stream processing; relational algebra; sensor data consistency; sensor data covariance; sensor data fusion; sensor data uncertainty; uncertainty processing; Algebra; Context; Context modeling; Current measurement; Measurement uncertainty; Mobile robots; Uncertainty; Context-aware services; Sensor fusion; Sensor systems and applications;
Conference_Titel :
Pervasive Computing and Communications Workshops (PERCOM Workshops), 2012 IEEE International Conference on
Conference_Location :
Lugano
Print_ISBN :
978-1-4673-0905-9
Electronic_ISBN :
978-1-4673-0906-6
DOI :
10.1109/PerComW.2012.6197574